Together AI· Inference platform

Together AI at ICML 2026: frontier research across the full stack

Nine papers is a lot to take in as a list. The better way to read them is by where they sit in the stack. Frontier AI is not built at a single layer. It is the product of research that runs from the agent down to the GPU kernel, and a gain at any one layer is wasted if the layers around it cannot keep up. This is at the core of how we work. From frontier agents at the top to kernels at the bottom, our research touches each one, and each layer feeds the next. The research becomes part of the Together platform, and the production workloads running on that platform point us to the next research problem. Aurora, our ICML paper on adaptive speculative decoding, is a clear example: the same line of work ships today as our ATLAS speculator in production. Here is this year's work, layer by layer, top down. 01 Frontier agents Agents that do real work — measured on tasks you can't fake your way through. DSGym 1,000+ tasks across 10+ domains ThunderAgent Up to 3.6× faster agent inference TTT-Discover Beats best human, open model 02 Model shaping Turning a base model into a reasoner — even where there's no answer key to check. RARO 25% win rate, no verifier V1 …

Announced

30 Jun 2026 00:00 UTC